Method for laser engraving of metal bond interface interlocking texture based on machine vision

Abstract

The application discloses a kind of metal bonding interface interlocking texture laser etching manufacturing methods based on machine vision, comprising the following steps: step S10: build processing platform;Step S20: using laser generator emits laser beam, and the surface of the workpiece being processed is carried out laser etching processing along preset trajectory;Step S30: using camera real-time shooting the surface texture image of the workpiece being processed;Step S40: surface texture image is preprocessed;Step S50: etching region feature identification is carried out to the surface texture image after preprocessing, and the edge position of etching recessed region is calibrated, and the recessed opening width is measured;Step S60: whether the recessed opening width is by big to small and gradually approaches laser focal point diameter, if yes, then stop next etching, end processing;If not, repeat step S20~Step S60.The metal bonding interface interlocking texture laser etching manufacturing method based on machine vision can effectively improve the accuracy of feature structure processing, intelligent degree and production efficiency.

Description

TECHNICAL FIELD

[0001] The present specification relates to the technical field of metal surface processing, and in particular to a laser etching manufacturing method for metal bonding interface interlocking texture based on machine vision. BACKGROUND

[0002] The description in this section is only provided for background information related to the disclosure of the present specification, and does not constitute prior art.

[0003] Metal bonding structure refers to a structure formed by bonding one metal material and the same or different materials together, which has the advantages of light weight, high strength, uniform stress distribution, etc., and has been widely used in the fields of aerospace, automobile, rail transportation, ship, electronics, building, etc. The interlocking of the metal-polymer interface during the bonding process can greatly improve the mechanical anchoring effect of the interface and significantly improve the mechanical properties of the bonding interface.

[0004] Making a necked inner cavity structure on the metal surface, i.e., the inner cavity opening width is smaller than the middle width, is a key prerequisite for preparing a metal-polymer interlocking interface. One method to improve the strength and fracture toughness of the metal bonding structure is to use laser to etch and process texture on the metal surface to be connected area, which not only increases the bonding area of the metal, but also can obtain an interlocking structure under certain laser parameters, thereby achieving the purpose of improving the bonding strength of the metal.

[0005] The mechanism of laser and metal surface is complex, and if the etching depth is insufficient, it is difficult to form a necked inner cavity structure, and if the etching depth is too large, it is easy to form bonding pores at the bottom of the inner cavity and reduce the stiffness of the metal matrix. Therefore, it is very important to accurately determine the moment when the interlocking structure appears and to control the processing action in real time. Therefore, it is particularly important to use machine vision method to realize online detection and control of laser etching for preparing metal surface texture.

[0006] It should be noted that the above introduction to the technical background is only to facilitate the clear and complete description of the technical scheme of the present specification, and to facilitate the understanding of those skilled in the art. The above technical scheme cannot be considered as known to those skilled in the art merely because it is described in the background section of the present specification. SUMMARY

[0007] In view of the deficiencies of the prior art, one object of the present specification is to provide a laser etching manufacturing method for metal bonding interface interlocking texture based on machine vision, which can realize online detection and closed-loop control of the manufacturing process of laser processing metal workpiece surface texture, and effectively improve the accuracy, intelligent degree and production efficiency of feature structure processing.

[0008] To achieve the above object, the embodiment of the present specification provides a laser etching manufacturing method of metal bonding interface interlocking texture based on machine vision, comprising the following steps:

[0009] Step S10: build a processing platform; the processing platform comprises a laser generator, a camera, a visual detection system functional module, a laser controller and a control part, the visual detection system functional module is respectively connected with the camera and the control part, and the laser controller is respectively connected with the laser generator and the control part;

[0010] Step S20: using the laser generator emits laser beam, along the preset trajectory to the surface of the workpiece for laser etching processing;

[0011] Step S30: using the camera to shoot the surface texture image of the workpiece in real time;

[0012] Step S40: pretreatment of the surface texture image;

[0013] Step S50: etching area feature recognition is carried out on the pretreated surface texture image, the edge position of etching recessed area is calibrated, and the opening width of the recess is measured;

[0014] Step S60: determine whether the recess opening width is from large to small and gradually approaches the diameter of laser focal point, if yes, stop etching next time, and end processing; if not, repeat steps S20-S60.

[0015] As a preferred embodiment, in the step S10, the processing platform further comprises a mechanical arm, the mechanical arm is connected with the control part; the camera is located on one side of the laser generator, and the camera and the laser generator are connected with the mechanical arm through a connecting part.

[0016] As a preferred embodiment, in the step S20, the mechanical arm is used to adjust the laser generator, so that the laser emitted by the laser generator is perpendicular to the surface of the workpiece, and the laser focal point emitted by the laser generator is gathered on the surface of the workpiece.

[0017] As a preferred embodiment, in the step S20, the workpiece is kept stationary, and the control part controls the mechanical arm to drive the laser generator to move for laser etching processing; or, the laser generator is kept stationary, and the workpiece moves for laser etching processing.

[0018] As a preferred implementation, the visual detection system function module comprises a camera parameter module, an image acquisition module and a feature detection module; the camera parameter module is used to adjust the parameters of the camera, including brightness, focal length, magnification, gain and color; the image acquisition module comprises an image acquisition unit, an image storage unit and an image viewing unit; the feature detection module comprises an image processing unit, a feature recognition unit and a feature width measurement unit.

[0019] As a preferred implementation, the laser generator comprises a continuous laser, a nanosecond laser, a picosecond laser or a femtosecond laser.

[0020] As a preferred implementation, the material of the workpiece to be processed comprises stainless steel, carbon steel, alloy steel, aluminum alloy, magnesium alloy and titanium alloy.

[0021] As a preferred implementation, the laser etching processing comprises pit etching and groove etching.

[0022] As a preferred implementation, the step S40 comprises:

[0023] Gray processing is performed on the surface texture image;

[0024] Median filtering method is used to perform denoising processing on the gray-processed surface texture image;

[0025] Threshold segmentation method is used to perform image segmentation on the denoised surface texture image, so as to separate the target feature from the background.

[0026] As a preferred implementation, the step S50 comprises:

[0027] Texture edge detection is performed;

[0028] Connected domain labeling is performed;

[0029] The average opening diameter of ten positions in the selected area is measured as the recess opening width.

[0030] Beneficial effects:

[0031] The laser etching manufacturing method for the metal bonding interface interlocking texture based on machine vision provided by the embodiment can realize intelligent manufacturing of the laser processing metal workpiece surface texture through the steps S10, S20, S30, S40, S50 and S60. Through real-time image acquisition, processing, feature recognition and feature size measurement of the laser etching metal surface, the laser etching preparation of the "necking" shape inner cavity of the metal surface is realized, the mechanical anchoring effect of the bonding interface is enhanced, and the interface strength and fracture toughness of the metal bonding structure can be significantly improved. Compared with artificial judgment of the feature structure, the feature structure detection by the machine vision means (camera) can effectively avoid human error and improve the processing accuracy. Further, the opening width of the laser processing texture is used to judge whether the necking structure appears, which is more efficient and faster than other judgment methods. The manufacturing method can realize the closed loop of laser processing metal workpiece surface texture detection and control, improve the accuracy of feature structure processing, save productivity and improve production efficiency.

[0032] Specific embodiments of the application are disclosed below with reference to the drawings, in which the principles of the application can be employed. It should be understood, however, that the embodiments of the application are not limited to the particular embodiments described herein but are amenable to various changes and modifications without departing from the scope of the application.

[0033] Features described and / or illustrated with respect to one implementation can be used in one or more other implementations in the same or similar manner, in combination with or in place of features in other implementations, and / or the like.

[0034] It should be emphasized that the term "comprises / comprising" when used in this specification is taken to specify the presence of stated features, integers, steps or components but does not preclude the presence or addition of one or more other features, integers, steps, components, or groups thereof. BRIEF DESCRIPTION OF DRAWINGS

[0035] In order to more clearly illustrate the technical solutions of the embodiments of the present application or the prior art, the drawings needed to be used in the following embodiment or prior art description will be briefly introduced. Obviously, the drawings in the following description only illustrate some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor.

[0036] Figure 1 A step flow chart of a laser etching manufacturing method for metal bonding interface interlocking texture based on machine vision provided in the embodiment;

[0037] Figure 2 A structure schematic diagram of a processing platform provided in the embodiment;

[0038] Figure 3Fig. 4 is a schematic diagram of the structure of the machined workpiece surface after laser machining according to an embodiment of the present application;

[0039] Figure 4 Fig. 5 is a surface texture image of the machined workpiece surface after laser machining according to an embodiment of the present application;

[0040] Figure 5 Fig. 6 is a schematic diagram of the structure of the machined workpiece surface after laser machining according to another embodiment of the present application; Figure 4 Fig. 7 is a corresponding diagram of the protrusion, groove and opening width at different machining times;

[0041] Figure 6 Fig. 8 is a diagram of the opening width variation with groove depth of a titanium alloy material during laser machining;

[0042] Figure 7 Fig. 9 is a diagram of the opening width variation with groove depth of a carbon steel material during laser machining.

[0043] BRIEF DESCRIPTION OF DRAWINGS

[0044] 1, mechanical arm; 2, laser controller; 3, laser camera integrated system; 301, laser generator; 302, camera; 303, connecting part; 4, visual detection system function module; 5, machined workpiece; 6, control part; 7, protrusion; 8, groove; w, opening width. DETAILED DESCRIPTION

[0045] In order to make the person skilled in the art better understand the technical solutions in the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by the person skilled in the art without creative labor should be within the scope of protection of the present application.

[0046] It should be noted that when an element is referred to as being "disposed on" another element, it can be directly on the other element or there can be a middle element. When an element is referred to as being "connected" to another element, it can be directly connected to the other element or there can be a middle element. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only and are not intended to be the only embodiment.

[0047] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0048] Please see Figure 1 This application provides a machine vision-based laser etching method for manufacturing interlocking textures at metal bonding interfaces, comprising the following steps:

[0049] Step S10: Set up the processing platform.

[0050] Among them, such as Figure 2 As shown, the processing platform includes a laser generator 301, a camera 302, a vision inspection system functional module 4, a laser controller 2, and a control unit 6. The vision inspection system functional module 4 is electrically connected to both the camera 302 and the control unit 6, and the laser controller 2 is electrically connected to both the laser generator 301 and the control unit 6. The laser controller 2 controls the laser parameters of the laser generator 301. The laser generator 301 processes the surface of the workpiece 5, and the camera 302 converts the surface texture light signal of the workpiece 5 into an electrical signal, thereby realizing image storage and display.

[0051] Step S20: Use the laser generator 301 to emit a laser beam and perform laser etching on the surface of the workpiece 5 along a preset trajectory.

[0052] Step S30: Use the camera 302 to capture a real-time image of the surface texture of the workpiece 5 being processed, such as... Figure 4 As shown.

[0053] Step S40: Preprocess the surface texture image.

[0054] Step S50: Perform etched area feature recognition on the preprocessed surface texture image, mark the edge position of the etched depression area, and measure the width w of the depression opening, such as... Figure 3 and Figure 5 As shown.

[0055] Step S60: Determine whether the width w of the recessed opening decreases from large to small and gradually approaches the diameter of the laser focal point. If so, stop the next etching and end the processing; otherwise, repeat steps S20 to S60.

[0056] The machine vision-based laser etching manufacturing method for interlocking textures at metal bonding interfaces provided in this embodiment, through steps S10, S20, S30, S40, S50, and S60, enables intelligent manufacturing of surface textures on laser-processed metal workpieces. By performing real-time image acquisition, processing, feature recognition, and feature dimension measurement on the laser-etched metal surface, the laser etching of "narrowed" shaped cavities on the metal surface is achieved, enhancing the mechanical anchoring effect of the bonding interface and significantly improving the interface strength and fracture toughness of the metal bonding components. Using machine vision (camera 302) for feature structure detection effectively avoids human error and improves processing accuracy compared to manual judgment. Furthermore, determining the presence of narrowed structures by the opening width w of the laser-processed texture is more efficient and faster than other judgment methods. This manufacturing method achieves a closed loop for surface texture detection and control of laser-processed metal workpieces, improving the accuracy of feature structure processing, saving productivity, and increasing production efficiency.

[0057] In this embodiment, in step S10, the processing platform further includes a robotic arm 1, which is electrically connected to the control unit 6, allowing the control unit 6 to control the movement of the robotic arm 1. The camera 302 is located on one side of the laser generator 301, and the camera 302 and the laser generator 301 are connected to the robotic arm 1 via a connecting part 303. Preferably, the robotic arm 1 is connected to a laser camera integrated system 3 via the connecting part 303, and the laser camera integrated system 3 includes a camera 302 and a laser generator 301. The control unit 6 is connected to the robotic arm 1, the laser controller 2, and the visual inspection system functional module 4. Based on the features obtained from image recognition, it performs online recognition of the embedded structure and then controls the robotic arm 1 and the laser controller 2. The robotic arm 1 can control the movement trajectory of the laser generator 301, and the laser controller 2 can control the laser parameters of the laser generator 301.

[0058] In step S20, the robotic arm 1 is used to adjust the laser generator 301 so that the laser emitted by the laser generator 301 is perpendicularly incident on the surface of the workpiece 5 being processed, and the laser emitted by the laser generator 301 is focused on the surface of the workpiece 5 being processed.

[0059] In this embodiment, in step S20, the workpiece 5 remains stationary, and the control unit 6 controls the robotic arm 1 to move the laser generator 301 to perform laser etching. In another embodiment, the robotic arm 1 is not connected to the laser generator 301, but is connected to the workpiece 5. During laser processing, the laser generator 301 remains stationary, and the workpiece 5 is moved by the robotic arm 1 to perform laser etching.

[0060] In this embodiment, the visual inspection system functional module 4 includes a camera parameter module, an image acquisition module, and a feature detection module. The camera parameter module is used to adjust the parameters of the camera 302, including brightness, focal length, magnification, gain, and color. The image acquisition module includes an image acquisition unit, an image storage unit, and an image viewing unit. The feature detection module includes an image processing unit, a feature recognition unit, and a feature width measurement unit.

[0061] Specifically, the laser generator 301 includes a continuous laser, a nanosecond laser, a picosecond laser, or a femtosecond laser. The material of the workpiece 5 being processed includes stainless steel, carbon steel, alloy steel, aluminum alloy, magnesium alloy, and titanium alloy. The laser etching process includes pit etching and groove etching.

[0062] In one specific embodiment, the interlocking texture of the bonding interface of the titanium alloy material is prepared using the above manufacturing method. Specifically, when the workpiece 5 is made of titanium alloy, a nanosecond laser is selected, and the camera 302 is an industrial microscope camera. The images acquired by this camera 302 are uncompressed, thus enabling the acquisition of high-quality RGB images. The lens of the camera 302 can be a standard lens or a telecentric lens. For metal workpieces with a small processing area, where sufficient field of view and higher magnification are required during observation, a telecentric lens can be selected.

[0063] In this example, the workpiece 5 is a titanium alloy sheet. Experiments have verified that under certain laser parameters, a constricted etching texture can be formed on the surface of the titanium alloy sheet, and a constricted inner cavity appears when the opening width w reaches a certain size. Therefore, the presence of a constricted inner cavity can be determined by observing the width of the etching texture.

[0064] In step S20, before laser metal surface texture processing, the surface layer of the entire metal workpiece is first removed by continuous laser etching to remove grease, rust, etc. from the material surface. Then, the processing contour trajectory pattern (i.e., the preset trajectory) is designed and imported, and the laser parameters are set.

[0065] In step S40, the surface texture image is preprocessed to improve image quality and increase the recognition rate of surface texture features. Step S40 specifically includes:

[0066] Step S401: Perform grayscale processing on the surface texture image.

[0067] Compared to color images, grayscale images occupy less memory, run faster, and can visually increase contrast. Since the human eye is most sensitive to green and least sensitive to blue, the three vectors R, G, and B are comprehensively considered using a weighted average method based on importance and other indicators. The final grayscale value g(i,j) is calculated as: g(i,j) = 0.3R(i,j) + 0.59G(i,j) + 0.11B(i,j).

[0068] Step S402: The grayscale processed surface texture image is denoised using a median filtering method.

[0069] Sort all pixels in descending order {x1, x2, ..., x} n}, thus obtaining the values ​​in the sequence:

[0070]

[0071] Use the median value y as the new grayscale value of the target pixel.

[0072] Step S403: Use threshold segmentation to segment the surface texture image after denoising, separating the target features from the background.

[0073] Specifically, pixels are divided into different subsets based on grayscale levels. Each subset corresponds to a different region in the image. A suitable threshold is selected based on the pixel values ​​of each subset to segment the target object from the background. This example uses a region growing method for threshold segmentation. First, a seed point is selected within the target region as the starting point for growth. Then, pixels in the neighboring region of the seed point are compared, and pixels that meet the growth rules are assigned to that region. This process is iterated until all pixels in the image with similar attributes to the target object belong to the same region.

[0074] In this embodiment, step S50 includes:

[0075] Step S501: Perform texture edge detection.

[0076] Specifically, leveraging the characteristic that edges are located at the boundary between the target object and the background, and are the regions with the most dramatic gray-level changes in an image, gradient-based edge detection is used to extract the edge contours of concave regions. More specifically, the Canny operator, which has advantages such as good edge detection performance and localization accuracy, is selected for edge detection.

[0077] Step S502: Perform connected component labeling.

[0078] Specifically, due to metal spatter and other effects during laser processing, some foreign objects may occasionally adhere to the edges of the acquired images. In this case, the texture contour obtained through edge detection will contain some independent pixel regions. A width-first search algorithm is used as input to the edge-detected image, and the algorithm traverses the entire image. First, all connected components in the image are marked, and then the largest connected component is found and output from the marked connected components.

[0079] Step S503: Measure the average opening diameter at ten locations within the selected area as the width w of the recessed opening.

[0080] Specifically, the average opening diameter d at ten locations within a selected area is measured using a horizontal multiline method within the software system. For example... Figure 6 As shown, when the average opening diameter d decreases to around 55mm and the opening width w stabilizes and no longer decreases significantly, it is determined that a narrowing structure has appeared, and the next processing should be stopped; otherwise, processing should continue.

[0081] In another specific embodiment, the interlocking texture of the bonding interface of carbon steel material is prepared using the above manufacturing method. Specifically, when the workpiece 5 is made of carbon steel, a nanosecond laser is selected. The operation steps are the same as in the previous embodiment (preparation of interlocking texture of the bonding interface of titanium alloy material). Figure 7 As shown, when the average opening diameter d decreases to around 60mm and the opening width w tends to stabilize and no longer decreases significantly, it is determined that a narrowing structure has appeared, and the next processing should be stopped; otherwise, processing should continue.

[0082] In this embodiment, the bonding surface of the workpiece 5 includes, but is not limited to, secondary bonding, co-curing bonding, metal-thermoplastic polymer laser welding, metal-thermoplastic polymer ultrasonic welding, metal-thermoplastic polymer induction welding, metal-prepreg molding, and other surfaces involving the bonding of metal and polymer. The thermoplastic polymer includes single thermoplastic polymers, blended thermoplastic polymers, fiber-reinforced thermoplastic polymers, and particle-reinforced thermoplastic polymers.

[0083] exist Figure 5 In the image, the adhesive is only for demonstration purposes. To make the protrusions 7 and grooves 8 more obvious, there is no adhesive in the actual surface texture image of the workpiece 5 taken by camera 302.

[0084] It should be noted that in the description of this specification, the terms "first," "second," etc., are used only for descriptive purposes and to distinguish similar objects; there is no order between them, nor should they be construed as indicating or implying relative importance. Furthermore, in the description of this specification, unless otherwise stated, "a plurality of" means two or more.

[0085] Any numerical values ​​cited herein include all values ​​ranging from a lower limit to an upper limit, increasing by one unit, with at least two units between any lower and any higher value. For example, if the quantity of a component or the value of a process variable (e.g., temperature, pressure, time, etc.) is described as being from 1 to 90, preferably from 20 to 80, more preferably from 30 to 70, the purpose is to illustrate that values ​​such as 15 to 85, 22 to 68, 43 to 51, 30 to 32 are also explicitly listed in this specification. For values ​​less than 1, a unit is appropriately considered to be 0.0001, 0.001, 0.01, 0.1, etc. These are merely examples intended for explicit expression, and it can be assumed that all possible combinations of values ​​listed between the minimum and maximum values ​​are similarly explicitly stated in this specification.

[0086] Unless otherwise stated, all ranges include the endpoints and all numbers between them. The terms "approximately" or "about" used with ranges apply to both endpoints of the range. Thus, "approximately 20 to 30" is intended to cover "approximately 20 to approximately 30," including at least the specified endpoints.

[0087] All articles and references disclosed herein, including patent applications and publications, are incorporated herein by reference for various purposes. The term “substantially constitutes…” used to describe a combination should include the identified elements, components, parts, or steps, as well as other elements, components, parts, or steps that do not substantially affect the essential novelty of the combination. The use of the terms “comprising” or “including” to describe combinations of elements, components, parts, or steps herein also contemplates embodiments substantially constituted by such elements, components, parts, or steps. The use of the term “may” herein is intended to indicate that any described attribute included by “may” is optional.

[0088] Multiple elements, components, parts, or steps can be provided by a single integrated element, component, part, or step. Alternatively, a single integrated element, component, part, or step can be divided into multiple separate elements, components, parts, or steps. The use of the word "a" or "an" to describe an element, component, part, or step does not imply the exclusion of other elements, components, parts, or steps.

[0089] It should be understood that the above description is for illustrative purposes and not for limitation. Many embodiments and applications beyond the provided examples will be apparent to those skilled in the art upon reading the above description. Therefore, the scope of this teaching should not be determined by reference to the above description, but rather by reference to the appended claims and the full scope of their equivalents. For purposes of completeness, all articles and references, including patent applications and publications, are incorporated herein by reference. The omission of any aspect of the subject matter disclosed herein in the preceding claims is not intended as a waiver of that subject matter, nor should it be construed as an indication that the inventors have not considered that subject matter as part of the disclosed inventive subject matter.

Claims

1. A machine vision-based laser etching method for manufacturing interlocking textures at metal bonding interfaces, characterized in that, Includes the following steps: Step S10: Build a processing platform; the processing platform includes a laser generator, a camera, a vision inspection system functional module, a laser controller, and a control unit. The vision inspection system functional module is electrically connected to the camera and the control unit, respectively, and the laser controller is electrically connected to the laser generator and the control unit, respectively. Step S20: Use the laser generator to emit a laser beam and perform laser etching on the surface of the workpiece along a preset trajectory; Step S30: Use the camera to capture a real-time image of the surface texture of the workpiece being processed; Step S40: Preprocess the surface texture image; Step S50: Perform etching region feature recognition on the preprocessed surface texture image, mark the edge position of the etching depression region, and measure the width of the depression opening; Step S60: Determine whether the width of the recessed opening decreases from large to small and gradually approaches the diameter of the laser focal point. If so, stop the next etching and end the processing; otherwise, repeat steps S20 to S60.

2. The laser etching manufacturing method for interlocking textures at metal bonding interfaces based on machine vision according to claim 1, characterized in that, In step S10, the processing platform further includes a robotic arm, which is electrically connected to the control unit; the camera is located on one side of the laser generator, and the camera and the laser generator are connected to the robotic arm via a connecting part.

3. The laser etching manufacturing method for interlocking textures at metal bonding interfaces based on machine vision according to claim 2, characterized in that, In step S20, the robotic arm is used to adjust the laser generator so that the laser emitted by the laser generator is perpendicularly incident on the surface of the workpiece being processed, and the laser emitted by the laser generator is focused on the surface of the workpiece being processed.

4. The laser etching manufacturing method for interlocking textures at metal bonding interfaces based on machine vision according to claim 2, characterized in that, In step S20, the workpiece being processed remains stationary, and the control unit controls the robotic arm to move the laser generator to perform laser etching; or, the laser generator remains stationary, and the workpiece being processed moves to perform laser etching.

5. The laser etching manufacturing method for interlocking textures at metal bonding interfaces based on machine vision according to claim 1, characterized in that, The visual inspection system includes a camera parameter module, an image acquisition module, and a feature detection module. The camera parameter module is used to adjust the parameters of the camera, including brightness, focal length, magnification, gain, and color. The image acquisition module includes an image acquisition unit, an image storage unit, and an image viewing unit. The feature detection module includes an image processing unit, a feature recognition unit, and a feature width measurement unit.

6. The laser etching manufacturing method for interlocking textures at metal bonding interfaces based on machine vision according to claim 1, characterized in that, The laser generator includes a continuous laser, a nanosecond laser, a picosecond laser, or a femtosecond laser.

7. The laser etching manufacturing method for interlocking textures at metal bonding interfaces based on machine vision according to claim 6, characterized in that, The materials of the workpiece being processed include stainless steel, carbon steel, alloy steel, aluminum alloy, magnesium alloy, and titanium alloy.

8. The laser etching manufacturing method for interlocking textures at metal bonding interfaces based on machine vision according to claim 6, characterized in that, The laser etching process includes pit etching and groove etching.

9. The laser etching manufacturing method for interlocking textures at metal bonding interfaces based on machine vision according to claim 1, characterized in that, Step S40 includes: Perform grayscale processing on the surface texture image; The grayscale processed surface texture image is denoised using a median filtering method. The surface texture image after denoising is segmented using a threshold segmentation method to separate the target features from the background.

10. The laser etching manufacturing method for interlocking textures at metal bonding interfaces based on machine vision according to claim 1, characterized in that, Step S50 includes: Perform texture edge detection; Perform connected component labeling; The average opening diameter at ten locations within the selected area is used as the width of the recessed opening.

Images